Personality and breast cancer screening in women of the GAZEL cohort study

Abstract

The potential benefit of breast cancer screening is mitigated by the risk of false positives and overdiagnosis, thus advocating for a more personalized approach, based on the individual benefit-harm balance. Since personality might influence the women's appraisal of this balance, this prospective observational cohort study examined whether it could influence mammography use. A total of 2691 postmenopausal women of the GAZEL Cohort Study completed the Bortner Type A Rating Scale and the Buss and Durkee Hostility Inventory in 1993. Associations between personality scores and subsequent mammography use, self-reported through up to five triennial follow-up questionnaires, were estimated with Odds Ratio (OR) and 95% confidence interval (CI) with logistic mixed model regressions, adjusting for age, occupational grade, marital status, family history of breast cancer, age at menarche, age at first delivery, gynecological follow-up, hormone therapy use, and depressive symptoms. Individual propensity scores were used to weight the analyses to control for potential selection biases. More than 90% of the participants completed at least two follow-up questionnaires. Type A personality, but not hostility, was associated with mammography use in both univariate (crude OR [95% CI]: 1.62 [1.24–2.11], P < 0.001) and multivariate analyses (OR [95% CI]: 1.46 [1.13–1.90], P < 0.01). Type A personality traits (i.e., sense of time urgency, high job involvement, competitiveness) independently predicted mammography use among postmenopausal women. While paying more attention to the adherence of women with low levels of these traits, clinicians may help those with higher levels to better consider the risks of false positives and overdiagnosis.

Type A personality traits (i.e., sense of time urgency, high job involvement, competitiveness) independently predicted mammography use among 2691 postmenopausal women of the GAZEL Cohort Study (adjusted Odds Ratio [95% confidence interval]: 1.46: [1.13–1.90], P < 0.01). While paying more attention to the adherence of women with low levels of these traits, clinicians may help those with higher levels to better consider the risks of false positives and overdiagnosis.

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